Optimization of multiclass queueing networks with changeover times via the achievable region method: Part II, the multi-station case

We address the problem of scheduling a multi-station multiclassqueueing network (MQNET) with server changeover times to minimizesteady-state mean job holding costs. We present new lower boundson the best achievable cost that emerge as the values ofmathematical programming problems (linear, semidefinite, andconvex) over relaxed formulations of the system's achievableperformance region. The constraints on achievable performancedefining these formulations are obtained by formulatingsystem's equilibrium relations. Our contributions include: (1) aflow conservation interpretation and closed formulae for theconstraints previously derived by the potential function method;(2) new work decomposition laws for MQNETs; (3) new constraints(linear, convex, and semidefinite) on the performance region offirst and second moments of queue lengths for MQNETs; (4) a fastbound for a MQNET with N customer classes computed in N steps; (5)two heuristic scheduling policies: a priority-index policy, anda policy extracted from the solution of a linear programmingrelaxation.

Emergence of Cooperation on Static and Dynamic Networks

Game theory is a branch of applied mathematics used to analyze situation where two or more agents are interacting. Originally it was developed as a model for conflicts and collaborations between rational and intelligent individuals. Now it finds applications in social sciences, eco- nomics, biology (particularly evolutionary biology and ecology), engineering, political science, international relations, computer science, and philosophy. Networks are an abstract representation of interactions, dependencies or relationships. Net- works are extensively used in all the fields mentioned above and in many more. Many useful informations about a system can be discovered by analyzing the current state of a network representation of such system. In this work we will apply some of the methods of game theory to populations of agents that are interconnected. A population is in fact represented by a network of players where one can only interact with another if there is a connection between them. In the first part of this work we will show that the structure of the underlying network has a strong influence on the strategies that the players will decide to adopt to maximize their utility. We will then introduce a supplementary degree of freedom by allowing the structure of the population to be modified along the simulations. This modification allows the players to modify the structure of their environment to optimize the utility that they can obtain.

Resistance to diet-induced obesity and associated metabolic perturbations in haploinsufficient monocarboxylate transporter 1 mice

The monocarboxylate transporter 1 (MCT1 or SLC16A1) is a carrier of short-chain fatty acids, ketone bodies, and lactate in several tissues. Genetically modified C57BL/6J mice were produced by targeted disruption of the mct1 gene in order to understand the role of this transporter in energy homeostasis. Null mutation was embryonically lethal, but MCT1 (+/-) mice developed normally. However, when fed high fat diet (HFD), MCT1 (+/-) mice displayed resistance to development of diet-induced obesity (24.8% lower body weight after 16 weeks of HFD), as well as less insulin resistance and no hepatic steatosis as compared to littermate MCT1 (+/+) mice used as controls. Body composition analysis revealed that reduced weight gain in MCT1 (+/-) mice was due to decreased fat accumulation (50.0% less after 9 months of HFD) notably in liver and white adipose tissue. This phenotype was associated with reduced food intake under HFD (12.3% less over 10 weeks) and decreased intestinal energy absorption (9.6% higher stool energy content). Indirect calorimetry measurements showed ∼ 15% increase in O2 consumption and CO2 production during the resting phase, without any changes in physical activity. Determination of plasma concentrations for various metabolites and hormones did not reveal significant changes in lactate and ketone bodies levels between the two genotypes, but both insulin and leptin levels, which were elevated in MCT1 (+/+) mice when fed HFD, were reduced in MCT1 (+/-) mice under HFD. Interestingly, the enhancement in expression of several genes involved in lipid metabolism in the liver of MCT1 (+/+) mice under high fat diet was prevented in the liver of MCT1 (+/-) mice under the same diet, thus likely contributing to the observed phenotype. These findings uncover the critical role of MCT1 in the regulation of energy balance when animals are exposed to an obesogenic diet.

Multinationals, technology networks and international takeovers

We formulate a knowlegde--based model of direct investment through mergers and acquisitions. M&As are realized to create comparative advantages by exploiting international synergies and appropriating local technology spillovers requiring geographical proximity, but can also represent a strategic response to the presence of a multinational rival. The takeover fee paid tends to increase with the strength of local spillovers which can thus work against multinationalization. Seller's bargaining power increases the takeover fee, but does not influence the investment decision. We characterize losers and winners from multinationalization, and show that foreign investment stimulates research but could result in a synergy trap reducing multinationals' profits.

Mycorrhizal ecology and evolution: the past, the present, and the future.

1406 I. 1407 II. 1408 III. 1410 IV. 1411 V. 1413 VI. 1416 VII. 1418 1418 References 1419 SUMMARY: Almost all land plants form symbiotic associations with mycorrhizal fungi. These below-ground fungi play a key role in terrestrial ecosystems as they regulate nutrient and carbon cycles, and influence soil structure and ecosystem multifunctionality. Up to 80% of plant N and P is provided by mycorrhizal fungi and many plant species depend on these symbionts for growth and survival. Estimates suggest that there are c. 50 000 fungal species that form mycorrhizal associations with c. 250 000 plant species. The development of high-throughput molecular tools has helped us to better understand the biology, evolution, and biodiversity of mycorrhizal associations. Nuclear genome assemblies and gene annotations of 33 mycorrhizal fungal species are now available providing fascinating opportunities to deepen our understanding of the mycorrhizal lifestyle, the metabolic capabilities of these plant symbionts, the molecular dialogue between symbionts, and evolutionary adaptations across a range of mycorrhizal associations. Large-scale molecular surveys have provided novel insights into the diversity, spatial and temporal dynamics of mycorrhizal fungal communities. At the ecological level, network theory makes it possible to analyze interactions between plant-fungal partners as complex underground multi-species networks. Our analysis suggests that nestedness, modularity and specificity of mycorrhizal networks vary and depend on mycorrhizal type. Mechanistic models explaining partner choice, resource exchange, and coevolution in mycorrhizal associations have been developed and are being tested. This review ends with major frontiers for further research.

Comment on recent modeling studies of astrocyte-neuron metabolic interactions.

Recent years have seen a surge in mathematical modeling of the various aspects of neuron-astrocyte interactions, and the field of brain energy metabolism is no exception in that regard. Despite the advent of biophysical models in the field, the long-lasting debate on the role of lactate in brain energy metabolism is still unresolved. Quite the contrary, it has been ported to the world of differential equations. Here, we summarize the present state of this discussion from the modeler's point of view and bring some crucial points to the attention of the non-mathematically proficient reader.

Metabolic labeling and protein linearization technology allow the study of proteins secreted by cultured cells in serum-containing media.

Supernatants from cell cultures (also called conditioned media, CMs) are commonly analyzed to study the pool of secreted proteins (secretome). To reduce the exogenous protein background, serum-free media are often used to obtain CMs. Serum deprivation, however, can severely affect cell viability and phenotype, including protein secretion. We present a strategy to analyze the proteins secreted by cells in fetal bovine serum-containing CMs, which combines the advantage of metabolic labeling and protein concentration linearization techniques. Incubation of CMs with a hexapeptide ligand library was used to reduce the dynamic range of the samples and led to the identification of 3 times more proteins than in untreated CM samples. Labeling with a deuterated amino acid was used to distinguish between cellular proteins and homologous bovine proteins contained in the medium. Application of the strategy to two breast cancer cell lines led to the identification of proteins secreted in different amounts and which could correlate with their varying degree of aggressiveness. Selected reaction monitoring (SRM)-based quantitation of three proteins of interest in the crude samples yielded data in good agreement with the results from concentration-equalized samples.

Energetic and metabolic cost of growth in Gambian infants.

The aim of the study was to measure the energy used for growth of healthy fullterm and breast-fed Gambian infants. The weight gain (WG) of 14 infants (mean age +/- SEM 17 +/- 1 d, weight 3.581 +/- 0.105 kg) was measured over a 2-week period; the energy intake (EI) from breast milk was assessed for 24 h in the middle of the study period by weighing the infant before and after each breast-feed. On the same day, sleeping energy expenditure (SEE) and respiratory quotient (RQ) were measured for 30 min on five occasions through the 24-h period. EI averaged 502 +/- 25 kJ/kg.d, and SEE 230 +/- 6 kJ/kg.d; thus, an average of 272 kJ/kg.d were available for physical activity and the energy stored for growth. The total energy spent by infants while sleeping and for periods of physical activity was calculated to be 1.7 x SEE. The mean RQ measured on five occasions averaged 0.879 +/- 0.009. SEE was correlated with WG (r = 0.747, P less than 0.005), with a slope of the regression line of 5.5 kJ/g; this value can be considered as an estimate of the energy spent for new tissue synthesis in the resting infant. The efficiency of weight gain was lower in this study (67%) than in studies conducted on fast-growing preterm infants or children recovering from malnutrition.

Dyadic pulsations as a signature of sustainability in correspondence networks

In this paper, we introduce the concept of dyadic pulsations as a measure of sustainability in online discussion groups. Dyadic pulsations correspond to new communication exchanges occurring between two participants in a discussion group. A group that continuously integrates new participants in the on-going conversation is characterized by a steady dyadic pulsation rhythm. On the contrary, groups that either pursue close conversation or unilateral communication have no or very little dyadic pulsations. We show on two examples taken from Usenet discussion groups, that dyadic pulsations permit to anticipate future bursts in response delay time which are signs of group discussion collapses. We discuss ways of making this measure resilient to spam and other common algorithmic production that pollutes real discussions

Buffer Capacity Allocation: A method to QoS support on MPLS networks

This paper describes an optimized model to support QoS by mean of Congestion minimization on LSPs (Label Switching Path). In order to perform this model, we start from a CFA (Capacity and Flow Allocation) model. As this model does not consider the buffer size to calculate the capacity cost, our model- named BCA (Buffer Capacity Allocation)- take into account this issue and it improve the CFA performance. To test our proposal, we perform several simulations; results show that BCA model minimizes LSP congestion and uniformly distributes flows on the network

Growth and metabolic activity of the extramatrical mycelium of endomycorrhizal maize plants

The objective of this experiment was to quantify the extramatrical mycelium of the arbuscular mycorrhizal (AM) fungus Glomus etunicatum (Becker & Gerdemann) grown on maize (Zea mays L. var. Piranão) provided with various levels of phosphate fertilizer and harvested at 30, 60 and 90 days after planting (DAP). Total extramatrical mycelium (TEM) was extracted from soil using a modified membrane filtration method, followed by quantification using a grid intersection technique. Active extramatrical mycelium (AEM) proportion was determined using an enzymatic method which measured dehydrogenase activity by following iodonitrotetrazolium reduction. At low levels of added P, there was relatively less TEM than at high levels of added P, but the AEM proportion at low soil P availability was significantly greater than at high soil P.

Connexins, diabetes and the metabolic syndrome.

Diabetes and the related metabolic syndrome are multi system disorders that result from improper interactions between various cell types. Even though the underlying mechanism remains to be fully understood, it is most likely that both the long and the short distance range cell interactions, which normally ensure the physiologic functioning of the pancreas, and its relationships with the insulin-targeted organs, are altered. This review focuses on the short-range type of interactions that depend on the contact between adjacent cells and, specifically, on the interactions that are dependent on connexins. The widespread distribution of these membrane proteins, their multiple modes of action, and their interactions with conditions/molecules associated to both the pathogenesis and the treatment of the 2 main forms of diabetes and the metabolic syndrome, make connexins an essential part of the chain of events that leads to metabolic diseases. Here, we review the present state of knowledge about the molecular and cell biology of the connexin genes and proteins, their general mechanisms of action, the roles specific connexin species play in the endocrine pancreas and the major insulin-targeted organs, under physiological and patho-physiological conditions.

Antiretroviral drug toxicity in relation to pharmacokinetics, metabolic profile and pharmacogenetics.

Introduction: Besides therapeutic effectiveness, drug tolerability is a key issue for treatments that must be taken indefinitely. Given the high prevalence of toxicity in HIV therapy, the factors implicated in drug-induced morbidities should be identified in order to improve the safety, tolerability and adherence to the treatments. Current approaches have focused almost exclusively on parent drug concentrations; whereas recent evidence suggests that drug metabolites resulting from complex genetic and environmental influences can also contribute to treatment outcome. Pharmacogenetic variations have shown to play a relevant role in the variability observed in antiretroviral drug exposure, clinical response and sometimes toxicity. The integration of pharmacokinetic, pharmacogenetic and metabolic determinants will more probably address current therapeutic needs in patients. Areas covered: This review offers a concise description of three classes of antiretroviral drugs. The review looks at the metabolic profile of these drugs and gives a comprehensive summary of the existing literature on the influence of pharmacogenetics on their pharmacokinetics and metabolic pathways, and the associated drug or metabolite toxicity. Expert opinion: Due to the high prevalence of toxicity and the related risk of low adherence to the treatments, association of kinetic, genetic and metabolic markers predictive of therapeutic or toxicity outcomes could represent a more complete approach for optimizing antiretroviral therapy.

Incremental neural networks for function approximation

A new strategy for incremental building of multilayer feedforward neural networks is proposed in the context of approximation of functions from R-p to R-q using noisy data. A stopping criterion based on the properties of the noise is also proposed. Experimental results for both artificial and real data are performed and two alternatives of the proposed construction strategy are compared.